Urban landscape genomics identifies fine-scale gene flow patterns in an avian invasive.

Low GW, Chattopadhyay B, Garg KM, Irestedt M, Ericson P, Yap G, Tang Q, Wu S, Rheindt FE

Heredity (Edinb) 120 (2) 138-153 [2018-01-00; online 2017-12-11]

Invasive species exert a serious impact on native fauna and flora and have been the target of many eradication and management efforts worldwide. However, a lack of data on population structure and history, exacerbated by the recency of many species introductions, limits the efficiency with which such species can be kept at bay. In this study we generated a novel genome of high assembly quality and genotyped 4735 genome-wide single nucleotide polymorphic (SNP) markers from 78 individuals of an invasive population of the Javan Myna Acridotheres javanicus across the island of Singapore. We inferred limited population subdivision at a micro-geographic level, a genetic patch size (~13-14 km) indicative of a pronounced dispersal ability, and barely an increase in effective population size since introduction despite an increase of four to five orders of magnitude in actual population size, suggesting that low population-genetic diversity following a bottleneck has not impeded establishment success. Landscape genomic analyses identified urban features, such as low-rise neighborhoods, that constitute pronounced barriers to gene flow. Based on our data, we consider an approach targeting the complete eradication of Javan Mynas across Singapore to be unfeasible. Instead, a mixed approach of localized mitigation measures taking into account urban geographic features and planning policy may be the most promising avenue to reducing the adverse impacts of this urban pest. Our study demonstrates how genomic methods can directly inform the management and control of invasive species, even in geographically limited datasets with high gene flow rates.

Bioinformatics Support for Computational Resources [Service]

NGI Stockholm (Genomics Applications) [Service]

NGI Stockholm (Genomics Production) [Service]

National Genomics Infrastructure [Service]

PubMed 29225353

DOI 10.1038/s41437-017-0026-1

Crossref 10.1038/s41437-017-0026-1

pii: 10.1038/s41437-017-0026-1
pmc: PMC5837122


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